Summary
We propose the adoption of the Additive on Imbalance Model, a refinement to Jupiter’s price impact mechanism designed to dampen slippage for smaller trades while preserving market efficiency and protecting JLP holders’ incentives.
This post outlines our recommended parameters for the model:
- Delta Imbalance Threshold
- Additive Factor
- Exponent
Alongside these parameters, we present projections on expected outcomes, including:
- Slippage for small, medium, and large trade sizes, exhibiting the impact on trader experience.
- Revenue profiles for JLP holders.
We welcome feedback from the community on these recommendations and their projected effects before moving to implementation.
Parameter Recommendations
In order to balance between financial security, user experience , and JLP holder revenue, we recommend setting the following risk parameters :
| Parameter | SOL | BTC | ETH |
|---|---|---|---|
| Delta Imbalance Threshold | 0.75e6 | 0.75e6 | 0.75e6 |
| Price Impact Factor | 1.0e-04 | 1.0e-04 | 1.0e-04 |
| Price Impact Exponent | 1 | 1 | 1 |
| Base Fee | 6 | 6 | 6 |
| Trade Impact Fee Scalar | 1.25e9 | 8e9 | 5e9 |
| Max Fee | 50bps | 50bps | 50bps |
Below are the projected Price Impact fees for different trade sizes and OI imbalances. For instance, if OI is $5M, a trade of $100K will pay a 13.6bps Price Impact Fee.
Impact on JLP holders
In order to provide some insights into the impact of parameter settings on JLP holders, we share here backtesting results of several configurations over 7 days of live trade data between March 26th and April 2nd, 2025, showing the projected total collected fees:
Summary
The proposed Additive on Imbalance Model offers a nuanced and data-driven improvement to Jupiter’s pricing logic, carefully designed to enhance the economic security while maintaining a good trader experience and protecting JLP holders.
By introducing a calibrated combination of Threshold, Factor, and Exponent, this model ensures a smooth gradient of slippage that aligns economic incentives across stakeholders. Our backtesting results demonstrate strong revenue preservation for JLPs even under more favorable conditions for traders.
We encourage the community to review the proposed parameters, examine the trade-off visualizations, and share feedback or alternative configurations.
Disclaimer
Chaos Labs has not been compensated by any third party for publishing this recommendation.
Copyright
Copyright and related rights waived via CC0